689 lines
21 KiB
Python
689 lines
21 KiB
Python
from enum import IntEnum
|
|
from logging import getLogger
|
|
from math import ceil
|
|
from typing import Any, Dict, List, Literal, Optional, Tuple, Union
|
|
|
|
from .models.meta import NetworkModel
|
|
from .torch_before_ort import GraphOptimizationLevel, SessionOptions
|
|
from .utils import coalesce
|
|
|
|
logger = getLogger(__name__)
|
|
|
|
|
|
Param = Union[str, int, float]
|
|
Point = Tuple[int, int]
|
|
UpscaleOrder = Literal["correction-first", "correction-last", "correction-both"]
|
|
UpscaleMethod = Literal["bilinear", "lanczos", "upscale"]
|
|
|
|
|
|
class SizeChart(IntEnum):
|
|
micro = 64
|
|
mini = 128 # small tile for very expensive models
|
|
half = 256 # half tile for outpainting
|
|
auto = 512 # auto tile size
|
|
hd1k = 2**10
|
|
hd2k = 2**11
|
|
hd4k = 2**12
|
|
hd8k = 2**13
|
|
hd16k = 2**14
|
|
hd32k = 2**15
|
|
hd64k = 2**16
|
|
max = 2**32 # should be a reasonable upper limit for now
|
|
|
|
|
|
class TileOrder:
|
|
grid = "grid"
|
|
kernel = "kernel"
|
|
spiral = "spiral"
|
|
|
|
|
|
class Border:
|
|
def __init__(self, left: int, right: int, top: int, bottom: int) -> None:
|
|
self.left = left
|
|
self.right = right
|
|
self.top = top
|
|
self.bottom = bottom
|
|
|
|
def __str__(self) -> str:
|
|
return "(%s, %s, %s, %s)" % (self.left, self.right, self.top, self.bottom)
|
|
|
|
def isZero(self) -> bool:
|
|
return all(
|
|
value == 0 for value in (self.left, self.right, self.top, self.bottom)
|
|
)
|
|
|
|
def tojson(self):
|
|
return {
|
|
"left": self.left,
|
|
"right": self.right,
|
|
"top": self.top,
|
|
"bottom": self.bottom,
|
|
}
|
|
|
|
def with_args(
|
|
self,
|
|
left: Optional[int] = None,
|
|
right: Optional[int] = None,
|
|
top: Optional[int] = None,
|
|
bottom: Optional[int] = None,
|
|
**kwargs,
|
|
):
|
|
logger.debug("ignoring extra kwargs for border: %s", kwargs)
|
|
return Border(
|
|
left or self.left,
|
|
right or self.right,
|
|
top or self.top,
|
|
bottom or self.bottom,
|
|
)
|
|
|
|
@classmethod
|
|
def even(cls, all: int):
|
|
return Border(all, all, all, all)
|
|
|
|
|
|
class Size:
|
|
def __init__(self, width: int, height: int) -> None:
|
|
self.width = width
|
|
self.height = height
|
|
|
|
def __iter__(self):
|
|
return iter([self.width, self.height])
|
|
|
|
def __str__(self) -> str:
|
|
return "%sx%s" % (self.width, self.height)
|
|
|
|
def __eq__(self, other: Any) -> bool:
|
|
if isinstance(other, Size):
|
|
return self.width == other.width and self.height == other.height
|
|
|
|
return False
|
|
|
|
def add_border(self, border: Border):
|
|
return Size(
|
|
border.left + self.width + border.right,
|
|
border.top + self.height + border.bottom,
|
|
)
|
|
|
|
def max(self, width: int, height: int):
|
|
return Size(max(self.width, width), max(self.height, height))
|
|
|
|
def min(self, width: int, height: int):
|
|
return Size(min(self.width, width), min(self.height, height))
|
|
|
|
def round_to_tile(self, tile=512):
|
|
return Size(
|
|
ceil(self.width / tile) * tile,
|
|
ceil(self.height / tile) * tile,
|
|
)
|
|
|
|
def tojson(self) -> Dict[str, int]:
|
|
return {
|
|
"width": self.width,
|
|
"height": self.height,
|
|
}
|
|
|
|
def with_args(
|
|
self,
|
|
height: Optional[int] = None,
|
|
width: Optional[int] = None,
|
|
**kwargs,
|
|
):
|
|
logger.debug("ignoring extra kwargs for size: %s", kwargs)
|
|
return Size(
|
|
width or self.width,
|
|
height or self.height,
|
|
)
|
|
|
|
|
|
class DeviceParams:
|
|
def __init__(
|
|
self,
|
|
device: str,
|
|
provider: str,
|
|
options: Optional[dict] = None,
|
|
optimizations: Optional[List[str]] = None,
|
|
) -> None:
|
|
self.device = device
|
|
self.provider = provider
|
|
self.options = options
|
|
self.optimizations = optimizations or []
|
|
self.sess_options_cache = None
|
|
|
|
def __str__(self) -> str:
|
|
return "%s - %s (%s)" % (self.device, self.provider, self.options)
|
|
|
|
def ort_provider(
|
|
self,
|
|
model_type: str,
|
|
suffix: Optional[str] = None,
|
|
) -> Union[str, Tuple[str, Any]]:
|
|
# check if model has been pinned to CPU
|
|
# TODO: check whether the CPU device is allowed
|
|
if f"onnx-cpu-{model_type}" in self.optimizations:
|
|
logger.debug("pinning %s to CPU", model_type)
|
|
return "CPUExecutionProvider"
|
|
|
|
if (
|
|
suffix is not None
|
|
and f"onnx-cpu-{model_type}-{suffix}" in self.optimizations
|
|
):
|
|
logger.debug("pinning %s-%s to CPU", model_type, suffix)
|
|
return "CPUExecutionProvider"
|
|
|
|
if self.options is None:
|
|
return self.provider
|
|
else:
|
|
return (self.provider, self.options)
|
|
|
|
def sess_options(self, cache=True) -> SessionOptions:
|
|
if cache and self.sess_options_cache is not None:
|
|
return self.sess_options_cache
|
|
|
|
sess = SessionOptions()
|
|
|
|
if "onnx-low-memory" in self.optimizations:
|
|
logger.debug("enabling ONNX low-memory optimizations")
|
|
sess.enable_cpu_mem_arena = False
|
|
sess.enable_mem_pattern = False
|
|
sess.enable_mem_reuse = False
|
|
|
|
if "onnx-graph-disable" in self.optimizations:
|
|
logger.debug("disabling all ONNX graph optimizations")
|
|
sess.graph_optimization_level = GraphOptimizationLevel.ORT_DISABLE_ALL
|
|
elif "onnx-graph-basic" in self.optimizations:
|
|
logger.debug("enabling basic ONNX graph optimizations")
|
|
sess.graph_optimization_level = GraphOptimizationLevel.ORT_ENABLE_BASIC
|
|
elif "onnx-graph-extended" in self.optimizations:
|
|
logger.debug("enabling extended ONNX graph optimizations")
|
|
sess.graph_optimization_level = GraphOptimizationLevel.ORT_ENABLE_EXTENDED
|
|
elif "onnx-graph-all" in self.optimizations:
|
|
logger.debug("enabling all ONNX graph optimizations")
|
|
sess.graph_optimization_level = GraphOptimizationLevel.ORT_ENABLE_ALL
|
|
|
|
if "onnx-deterministic-compute" in self.optimizations:
|
|
logger.debug("enabling ONNX deterministic compute")
|
|
sess.use_deterministic_compute = True
|
|
|
|
if cache:
|
|
self.sess_options_cache = sess
|
|
|
|
return sess
|
|
|
|
def torch_str(self) -> str:
|
|
if self.device.startswith("cuda"):
|
|
if self.options is not None and "device_id" in self.options:
|
|
return f"{self.device}:{self.options['device_id']}"
|
|
|
|
return self.device
|
|
elif self.device.startswith("rocm"):
|
|
if self.options is not None and "device_id" in self.options:
|
|
return f"cuda:{self.options['device_id']}"
|
|
|
|
return "cuda"
|
|
else:
|
|
return "cpu"
|
|
|
|
|
|
class ImageParams:
|
|
model: str
|
|
pipeline: str
|
|
scheduler: str
|
|
prompt: str
|
|
cfg: float
|
|
steps: int
|
|
seed: int
|
|
negative_prompt: Optional[str]
|
|
eta: float
|
|
batch: int
|
|
control: Optional[NetworkModel]
|
|
input_prompt: str
|
|
input_negative_prompt: Optional[str]
|
|
loopback: int
|
|
tiled_vae: bool
|
|
unet_tile: int
|
|
unet_overlap: float
|
|
vae_tile: int
|
|
vae_overlap: float
|
|
denoise: int
|
|
thumbnail: int
|
|
|
|
def __init__(
|
|
self,
|
|
model: str,
|
|
pipeline: str,
|
|
scheduler: str,
|
|
prompt: str,
|
|
cfg: float,
|
|
steps: int,
|
|
seed: int,
|
|
negative_prompt: Optional[str] = None,
|
|
eta: float = 0.0,
|
|
batch: int = 1,
|
|
control: Optional[NetworkModel] = None,
|
|
input_prompt: Optional[str] = None,
|
|
input_negative_prompt: Optional[str] = None,
|
|
loopback: int = 0,
|
|
tiled_vae: bool = False,
|
|
unet_overlap: float = 0.25,
|
|
unet_tile: int = 512,
|
|
vae_overlap: float = 0.25,
|
|
vae_tile: int = 512,
|
|
denoise: int = 3,
|
|
thumbnail: int = 1,
|
|
) -> None:
|
|
self.model = model
|
|
self.pipeline = pipeline
|
|
self.scheduler = scheduler
|
|
self.prompt = prompt
|
|
self.cfg = cfg
|
|
self.steps = steps
|
|
self.seed = seed
|
|
self.negative_prompt = negative_prompt
|
|
self.eta = eta
|
|
self.batch = batch
|
|
self.control = control
|
|
self.input_prompt = input_prompt or prompt
|
|
self.input_negative_prompt = input_negative_prompt or negative_prompt
|
|
self.loopback = loopback
|
|
self.tiled_vae = tiled_vae
|
|
self.unet_overlap = unet_overlap
|
|
self.unet_tile = unet_tile
|
|
self.vae_overlap = vae_overlap
|
|
self.vae_tile = vae_tile
|
|
self.denoise = denoise
|
|
self.thumbnail = thumbnail
|
|
|
|
def do_cfg(self):
|
|
return self.cfg > 1.0
|
|
|
|
def get_valid_pipeline(self, group: str, pipeline: Optional[str] = None) -> str:
|
|
pipeline = pipeline or self.pipeline
|
|
|
|
# if the correct pipeline was already requested, simply use that
|
|
if group == pipeline:
|
|
return pipeline
|
|
|
|
# otherwise, check for additional allowed pipelines
|
|
if group == "img2img":
|
|
if pipeline in [
|
|
"controlnet",
|
|
"img2img-sdxl",
|
|
"lpw",
|
|
"panorama",
|
|
"panorama-sdxl",
|
|
"pix2pix",
|
|
]:
|
|
return pipeline
|
|
elif pipeline == "txt2img-sdxl":
|
|
return "img2img-sdxl"
|
|
elif group == "inpaint":
|
|
if pipeline in ["controlnet", "lpw", "panorama"]:
|
|
return pipeline
|
|
elif group == "txt2img":
|
|
if pipeline in ["lpw", "panorama", "panorama-sdxl", "txt2img-sdxl"]:
|
|
return pipeline
|
|
|
|
logger.debug("pipeline %s is not valid for %s", pipeline, group)
|
|
return group
|
|
|
|
def is_control(self):
|
|
return self.pipeline in ["controlnet", "controlnet-sdxl"]
|
|
|
|
def is_lpw(self):
|
|
return self.pipeline == "lpw"
|
|
|
|
def is_panorama(self):
|
|
return self.pipeline in ["panorama", "panorama-sdxl"]
|
|
|
|
def is_pix2pix(self):
|
|
return self.pipeline == "pix2pix"
|
|
|
|
def is_xl(self):
|
|
return self.pipeline.endswith("-sdxl")
|
|
|
|
def tojson(self) -> Dict[str, Optional[Param]]:
|
|
return {
|
|
"model": self.model,
|
|
"pipeline": self.pipeline,
|
|
"scheduler": self.scheduler,
|
|
"prompt": self.prompt,
|
|
"negative_prompt": self.negative_prompt,
|
|
"cfg": self.cfg,
|
|
"seed": self.seed,
|
|
"steps": self.steps,
|
|
"eta": self.eta,
|
|
"batch": self.batch,
|
|
"control": self.control.name if self.control is not None else "",
|
|
"input_prompt": self.input_prompt,
|
|
"input_negative_prompt": self.input_negative_prompt,
|
|
"loopback": self.loopback,
|
|
"tiled_vae": self.tiled_vae,
|
|
"unet_overlap": self.unet_overlap,
|
|
"unet_tile": self.unet_tile,
|
|
"vae_overlap": self.vae_overlap,
|
|
"vae_tile": self.vae_tile,
|
|
"denoise": self.denoise,
|
|
"thumbnail": self.thumbnail,
|
|
}
|
|
|
|
def with_args(self, **kwargs):
|
|
return ImageParams(
|
|
kwargs.get("model", self.model),
|
|
kwargs.get("pipeline", self.pipeline),
|
|
kwargs.get("scheduler", self.scheduler),
|
|
kwargs.get("prompt", self.prompt),
|
|
kwargs.get("cfg", self.cfg),
|
|
kwargs.get("steps", self.steps),
|
|
kwargs.get("seed", self.seed),
|
|
kwargs.get("negative_prompt", self.negative_prompt),
|
|
kwargs.get("eta", self.eta),
|
|
kwargs.get("batch", self.batch),
|
|
kwargs.get("control", self.control),
|
|
kwargs.get("input_prompt", self.input_prompt),
|
|
kwargs.get("input_negative_prompt", self.input_negative_prompt),
|
|
kwargs.get("loopback", self.loopback),
|
|
kwargs.get("tiled_vae", self.tiled_vae),
|
|
kwargs.get("unet_overlap", self.unet_overlap),
|
|
kwargs.get("unet_tile", self.unet_tile),
|
|
kwargs.get("vae_overlap", self.vae_overlap),
|
|
kwargs.get("vae_tile", self.vae_tile),
|
|
kwargs.get("denoise", self.denoise),
|
|
kwargs.get("thumbnail", self.thumbnail),
|
|
)
|
|
|
|
|
|
class StageParams:
|
|
"""
|
|
Parameters for a chained pipeline stage
|
|
"""
|
|
|
|
def __init__(
|
|
self,
|
|
name: Optional[str] = None,
|
|
outscale: int = 1,
|
|
tile_order: str = TileOrder.spiral,
|
|
tile_size: int = SizeChart.auto,
|
|
# batch_size: int = 1,
|
|
) -> None:
|
|
self.name = name
|
|
self.outscale = outscale
|
|
self.tile_order = tile_order
|
|
self.tile_size = tile_size
|
|
|
|
def with_args(
|
|
self,
|
|
name: Optional[str] = None,
|
|
outscale: Optional[int] = None,
|
|
tile_order: Optional[str] = None,
|
|
tile_size: Optional[int] = None,
|
|
**kwargs,
|
|
):
|
|
logger.debug("ignoring extra kwargs for stage: %s", kwargs)
|
|
return StageParams(
|
|
name=coalesce(name, self.name),
|
|
outscale=coalesce(outscale, self.outscale),
|
|
tile_order=coalesce(tile_order, self.tile_order),
|
|
tile_size=coalesce(tile_size, self.tile_size),
|
|
)
|
|
|
|
|
|
class UpscaleParams:
|
|
def __init__(
|
|
self,
|
|
upscale_model: str,
|
|
correction_model: Optional[str] = None,
|
|
denoise: float = 0.5,
|
|
upscale=True,
|
|
faces=True,
|
|
face_outscale: int = 1,
|
|
face_strength: float = 0.5,
|
|
outscale: int = 1,
|
|
scale: int = 4,
|
|
pre_pad: int = 0,
|
|
tile_pad: int = 10,
|
|
upscale_order: UpscaleOrder = "correction-first",
|
|
) -> None:
|
|
self.upscale_model = upscale_model
|
|
self.correction_model = correction_model
|
|
self.denoise = denoise
|
|
self.upscale = upscale
|
|
self.faces = faces
|
|
self.face_outscale = face_outscale
|
|
self.face_strength = face_strength
|
|
self.outscale = outscale
|
|
self.pre_pad = pre_pad
|
|
self.scale = scale
|
|
self.tile_pad = tile_pad
|
|
self.upscale_order = upscale_order
|
|
|
|
def rescale(self, scale: int):
|
|
return UpscaleParams(
|
|
self.upscale_model,
|
|
correction_model=self.correction_model,
|
|
denoise=self.denoise,
|
|
upscale=self.upscale,
|
|
faces=self.faces,
|
|
face_outscale=self.face_outscale,
|
|
face_strength=self.face_strength,
|
|
outscale=scale,
|
|
scale=scale,
|
|
pre_pad=self.pre_pad,
|
|
tile_pad=self.tile_pad,
|
|
upscale_order=self.upscale_order,
|
|
)
|
|
|
|
def resize(self, size: Size) -> Size:
|
|
face_outscale = self.face_outscale
|
|
if self.upscale_order == "correction-both":
|
|
face_outscale *= self.face_outscale
|
|
|
|
return Size(
|
|
size.width * self.outscale * face_outscale,
|
|
size.height * self.outscale * face_outscale,
|
|
)
|
|
|
|
def tojson(self):
|
|
return {
|
|
"upscale_model": self.upscale_model,
|
|
"correction_model": self.correction_model,
|
|
"denoise": self.denoise,
|
|
"upscale": self.upscale,
|
|
"faces": self.faces,
|
|
"face_outscale": self.face_outscale,
|
|
"face_strength": self.face_strength,
|
|
"outscale": self.outscale,
|
|
"pre_pad": self.pre_pad,
|
|
"scale": self.scale,
|
|
"tile_pad": self.tile_pad,
|
|
"upscale_order": self.upscale_order,
|
|
}
|
|
|
|
def with_args(
|
|
self,
|
|
upscale_model: Optional[str] = None,
|
|
correction_model: Optional[str] = None,
|
|
denoise: Optional[float] = None,
|
|
upscale: Optional[bool] = None,
|
|
faces: Optional[bool] = None,
|
|
face_outscale: Optional[int] = None,
|
|
face_strength: Optional[float] = None,
|
|
outscale: Optional[int] = None,
|
|
scale: Optional[int] = None,
|
|
pre_pad: Optional[int] = None,
|
|
tile_pad: Optional[int] = None,
|
|
upscale_order: Optional[UpscaleOrder] = None,
|
|
**kwargs,
|
|
):
|
|
logger.debug("ignoring extra kwargs for upscale: %s", kwargs)
|
|
return UpscaleParams(
|
|
upscale_model=coalesce(upscale_model, self.upscale_model),
|
|
correction_model=coalesce(correction_model, self.correction_model),
|
|
denoise=coalesce(denoise, self.denoise),
|
|
upscale=coalesce(upscale, self.upscale),
|
|
faces=coalesce(faces, self.faces),
|
|
face_outscale=coalesce(face_outscale, self.face_outscale),
|
|
face_strength=coalesce(face_strength, self.face_strength),
|
|
outscale=coalesce(outscale, self.outscale),
|
|
scale=coalesce(scale, self.scale),
|
|
pre_pad=coalesce(pre_pad, self.pre_pad),
|
|
tile_pad=coalesce(tile_pad, self.tile_pad),
|
|
upscale_order=coalesce(upscale_order, self.upscale_order),
|
|
)
|
|
|
|
|
|
class HighresParams:
|
|
def __init__(
|
|
self,
|
|
enabled: bool,
|
|
scale: int,
|
|
steps: int,
|
|
strength: float,
|
|
method: UpscaleMethod = "lanczos",
|
|
iterations: int = 1,
|
|
):
|
|
self.enabled = enabled
|
|
self.scale = scale
|
|
self.steps = steps
|
|
self.strength = strength
|
|
self.method = method
|
|
self.iterations = iterations
|
|
|
|
def outscale(self) -> int:
|
|
return self.scale**self.iterations
|
|
|
|
def resize(self, size: Size) -> Size:
|
|
outscale = self.outscale()
|
|
return Size(
|
|
size.width * outscale,
|
|
size.height * outscale,
|
|
)
|
|
|
|
def tojson(self):
|
|
return {
|
|
"enabled": self.enabled,
|
|
"iterations": self.iterations,
|
|
"method": self.method,
|
|
"scale": self.scale,
|
|
"steps": self.steps,
|
|
"strength": self.strength,
|
|
}
|
|
|
|
def with_args(
|
|
self,
|
|
enabled: Optional[bool] = None,
|
|
scale: Optional[int] = None,
|
|
steps: Optional[int] = None,
|
|
strength: Optional[float] = None,
|
|
method: Optional[UpscaleMethod] = None,
|
|
iterations: Optional[int] = None,
|
|
**kwargs,
|
|
):
|
|
logger.debug("ignoring extra kwargs for highres: %s", kwargs)
|
|
return HighresParams(
|
|
enabled=coalesce(enabled, self.enabled),
|
|
scale=coalesce(scale, self.scale),
|
|
steps=coalesce(steps, self.steps),
|
|
strength=coalesce(strength, self.strength),
|
|
method=coalesce(method, self.method),
|
|
iterations=coalesce(iterations, self.iterations),
|
|
)
|
|
|
|
|
|
class LatentSymmetryParams:
|
|
enabled: bool
|
|
gradient_start: float
|
|
gradient_end: float
|
|
line_of_symmetry: float
|
|
|
|
def __init__(
|
|
self,
|
|
enabled: bool,
|
|
gradient_start: float,
|
|
gradient_end: float,
|
|
line_of_symmetry: float,
|
|
) -> None:
|
|
self.enabled = enabled
|
|
self.gradient_start = gradient_start
|
|
self.gradient_end = gradient_end
|
|
self.line_of_symmetry = line_of_symmetry
|
|
|
|
|
|
class PromptEditingParams:
|
|
enabled: bool
|
|
filter: str
|
|
remove_tokens: str
|
|
add_suffix: str
|
|
min_length: int
|
|
|
|
def __init__(
|
|
self,
|
|
enabled: bool,
|
|
filter: str,
|
|
remove_tokens: str,
|
|
add_suffix: str,
|
|
min_length: int,
|
|
) -> None:
|
|
self.enabled = enabled
|
|
self.filter = filter
|
|
self.remove_tokens = remove_tokens
|
|
self.add_suffix = add_suffix
|
|
self.min_length = min_length
|
|
|
|
|
|
class ExperimentalParams:
|
|
latent_symmetry: LatentSymmetryParams
|
|
prompt_editing: PromptEditingParams
|
|
|
|
def __init__(
|
|
self,
|
|
latent_symmetry: LatentSymmetryParams,
|
|
prompt_editing: PromptEditingParams,
|
|
) -> None:
|
|
self.latent_symmetry = latent_symmetry
|
|
self.prompt_editing = prompt_editing
|
|
|
|
|
|
class RequestParams:
|
|
device: DeviceParams
|
|
image: ImageParams
|
|
size: Optional[Size]
|
|
border: Optional[Border]
|
|
upscale: Optional[UpscaleParams]
|
|
highres: Optional[HighresParams]
|
|
experimental: Optional[ExperimentalParams]
|
|
|
|
def __init__(
|
|
self,
|
|
device: DeviceParams,
|
|
image: ImageParams,
|
|
size: Optional[Size] = None,
|
|
border: Optional[Border] = None,
|
|
upscale: Optional[UpscaleParams] = None,
|
|
highres: Optional[HighresParams] = None,
|
|
experimental: Optional[ExperimentalParams] = None,
|
|
) -> None:
|
|
self.device = device
|
|
self.image = image
|
|
self.size = size
|
|
self.border = border
|
|
self.upscale = upscale
|
|
self.highres = highres
|
|
self.experimental = experimental
|
|
|
|
|
|
def get_size(val: Union[int, str, None]) -> Union[int, SizeChart]:
|
|
if val is None:
|
|
return SizeChart.auto
|
|
|
|
if type(val) is int:
|
|
return val
|
|
|
|
if type(val) is str:
|
|
for size in SizeChart:
|
|
if val == size.name:
|
|
return size
|
|
|
|
return int(val)
|
|
|
|
raise ValueError("invalid size")
|